8 citations · 34 across the 59 of their papers we have counts for
65 papers
LeRF: Learning Reference Coordinate Frames for Perspective Taking Reasoning
Bang Xiao, Wenqi Jia, Ozgur Kara +5
Perspective taking is a fundamental component of spatial intelligence, requiring models interpret spatial relations from a specified viewpoint, such as that of another entity or an…
Thinking in Pictures: A Systematic Benchmark for Reasoning-driven Image Generation
Yutong Liu, Nan Huang, Xu Cao +1
Recent advancements in unified generative models (UGMs) and world simulators have achieved unprecedented results in visual perception and synthesis. However, these models primarily…
Kirin: Animal Motion Generation from In-the-Wild Video
Brian Nlong Zhao, Zhuoyang Pan, James M. Rehg +2
Understanding animal motion is fundamental to modeling animal behavior and biomechanics, yet progress in this area lags far behind human motion research due to the scarcity of high…
ConvDeck: Conversational Paper-to-Slide Generation via Stage-Specific User Feedback
Tarik Can Ozden, Sachidanand VS, Furkan Horoz +4
Automatic academic paper-to-slide generation is inherently iterative, because creating an effective presentation requires repeated cycles of generation, critique, and revision. Rec…
A Survey on Adversarial Attacks and Defenses for Diffusion Models Across Multiple Modalities
Ozgur Kara, Tarik Can Ozden, Furkan Horoz +6
Diffusion models have become the dominant family of generative models in the visual domain. However, their widespread public availability enables misuse at scale, motivating a rapi…
Decoding Children's Gait Behavior
Yifan Shen, Boyi Li, Meihuan Huang +12
We introduce a new problem domain for human action recognition: the fine-grained analysis of children's gait behaviors from standard RGB video. We specifically target the ambulator…
CogniRoute: Learning to Route Social Evidence in Omni-Modal Models
Yifan Shen, Pei Tian, Xinzhuo Li +8
Omni-modal models can ingest video, audio, and text, but unified access to multiple modalities does not guarantee that a model uses the right evidence. This gap is especially prono…
Exact Posterior Score Estimation for Solving Linear Inverse Problems
Abbas Mammadov, Ozgur Kara, Kaan Oktay +5
Diffusion and flow-based models learn powerful data priors by training a denoiser to reverse Gaussian corruption. To use this prior to solve a linear inverse problem, one needs to…
ST-DiffEye: Diffusion-based Continuous Gaze Generation via Joint Scanpath-Trajectory Modeling
Brian Nlong Zhao, Ozgur Kara, Junho Kim +1
We study the problem of human gaze modeling, which aims to generate the gaze patterns a viewer produces while observing a visual stimulus. Gaze is primarily captured through two mo…
When Eyes Betray AI: Social Gaze Consistency as a Semantic Cue for AI-Generated Image Detection
Jihyeon Kim, Sohee Kim, Soosan Lee +3
Recent generative models have largely closed the gap on low-level artifacts - pixel fingerprints, frequency anomalies, upsampling traces - particularly in person-centric and partia…
GRASP: Learning to Ground Social Reasoning in Multi-Person Non-Verbal Interactions
Junho Kim, Xu Cao, Houze Yang +6
Understanding social interactions requires reasoning over subtle non-verbal cues, yet current multimodal large language models (MLLMs) often fail to identify who interacts with who…
Towards a General Intelligence and Interface for Wearable Health Data
Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari +37
While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challeng…
IAM: Identity-Aware Human Motion and Shape Joint Generation
Wenqi Jia, Zekun Li, Abhay Mittal +6
Recent advances in text-driven human motion generation enable models to synthesize realistic motion sequences from natural language descriptions. However, most existing approaches…
Narrative-Driven Paper-to-Slide Generation via ArcDeck
Tarik Can Ozden, Sachidanand VS, Furkan Horoz +3
We introduce ArcDeck, a multi-agent framework that formulates paper-to-slide generation as a structured narrative reconstruction task. Unlike existing methods that directly summari…
Immune2V: Image Immunization Against Dual-Stream Image-to-Video Generation
Zeqian Long, Ozgur Kara, Haotian Xue +2
Image-to-video (I2V) generation has the potential for societal harm because it enables the unauthorized animation of static images to create realistic deepfakes. While existing def…
Self-Improving 4D Perception via Self-Distillation
Nan Huang, Pengcheng Yu, Weijia Zeng +4
Large-scale multi-view reconstruction models have made remarkable progress, but most existing approaches still rely on fully supervised training with ground-truth 3D/4D annotations…
STRIDE: When to Speak Meets Sequence Denoising for Streaming Video Understanding
Junho Kim, Hosu Lee, James M. Rehg +2
Recent progress in video large language models (Video-LLMs) has enabled strong offline reasoning over long and complex videos. However, real-world deployments increasingly require…
EgoForge: Goal-Directed Egocentric World Simulator
Yifan Shen, Jiateng Liu, Xinzhuo Li +9
Generative world models have shown promise for simulating dynamic environments, yet egocentric video remains challenging due to rapid viewpoint changes, frequent hand-object intera…
Vinedresser3D: Agentic Text-guided 3D Editing
Yankuan Chi, Xiang Li, Zixuan Huang +1
Text-guided 3D editing aims to modify existing 3D assets using natural-language instructions. Current methods struggle to jointly understand complex prompts, automatically localize…
Toward Cognitive Supersensing in Multimodal Large Language Model
Boyi Li, Yifan Shen, Yuanzhe Liu +12
Multimodal Large Language Models (MLLMs) have achieved remarkable success in open-vocabulary perceptual tasks, yet their ability to solve complex cognitive problems remains limited…
How Much 3D Do Video Foundation Models Encode?
Zixuan Huang, Xiang Li, Zhaoyang Lv +1
Videos are continuous 2D projections of 3D worlds. After training on large video data, will global 3D understanding naturally emerge? We study this by quantifying the 3D understand…
Toward Diffusible High-Dimensional Latent Spaces: A Frequency Perspective
Bolin Lai, Xudong Wang, Saketh Rambhatla +4
Latent diffusion has become the default paradigm for visual generation, yet we observe a persistent reconstruction-generation trade-off as latent dimensionality increases: higher-c…
Cue3D: Quantifying the Role of Image Cues in Single-Image 3D Generation
Xiang Li, Zirui Wang, Zixuan Huang +1
Humans and traditional computer vision methods rely on a diverse set of monocular cues to infer 3D structure from a single image, such as shading, texture, silhouette, etc. While r…
Layer-Aware Video Composition via Split-then-Merge
Ozgur Kara, Yujia Chen, Ming-Hsuan Yang +3
We present Split-then-Merge (StM), a novel framework designed to enhance control in generative video composition and address its data scarcity problem. Unlike conventional methods…